Conformational analysis using distance geometry methods

Abstract

Distance geometry methods have been used extensively to build models of molecules of various sizes, including small molecules, peptides, and proteins. These methods are often overlooked as tools for conformational analysis, even though they often perform as well as other conformational sampling methods. We have implemented two new distance geometry approaches in the DGEOM95 package. In the first new method, the traditional embedding algorithm is replaced with a procedure that generates random 4D coordinates for each atom, followed by refinement of these coordinates into 3D using the distance geometry error function. The conformational sampling produced by this method is comparable to that obtained with partial metrization, and superior to that obtained with the original embedding procedure. In the second method, a molecular dynamics step is included in the refinement stage. Although this method can be applied to any embedding algorithm, substantial improvements in sampling are seen primarily with the original embedding algorithm.